Falling Creek

Checking the difference between the top and the bottom

Checking the Winter timeseries for when the difference between the top and the bottom is greater than -0.1. The red line “inverse” is the 1m thermistor minus the 9m thermistor while “inverse 2” is the surface thermistor minus the 9m thermistor. The red dotted line is at -0.1 because the accuracy of the thermistors is 0.075.

After looking at the the timeseries let’s break it down for each period and look more closely at the temperature profiles, disolved oxygen profiles, and images from the camera at the catwalk.

When was the first day of Ice on in December

profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2022-12-22 00:00:00",
           end_time = "2023-01-05 00:00:00",
           Varibles = starts_with("Thermis"))
## Warning: Using an external vector in selections was deprecated in tidyselect 1.1.0.
## ℹ Please use `all_of()` or `any_of()` instead.
##   # Was:
##   data %>% select(Varibles)
## 
##   # Now:
##   data %>% select(all_of(Varibles))
## 
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

# DO
profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2022-12-22 00:00:00",
           end_time = "2023-01-05 00:00:00",
           Varibles = c("RDOsat_percent_5", "RDOsat_percent_9", "EXODOsat_percent_1"))

Pretty clear inverse stratification from about Dec. 23 to January 2nd.

It looks like we see ice on the camera on Dec. 25th

Thin layer of ice on the reservoir

When did ice come off at the beginning of January 2023

profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2022-12-31 00:00:00",
           end_time = "2023-01-05 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2022-12-22 00:00:00",
           end_time = "2023-01-05 00:00:00",
           Varibles = c("RDOsat_percent_5", "RDOsat_percent_9", "EXODOsat_percent_1"))

It looks like there is no longer inverse stratification on some time on January 2nd. Let’s look at the pictures

There could be faint ice in the backaground

Don’t see any ice in this picture and getting warm

Let’s check out the ice on and off from January 15th - January 17th

profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2023-01-15 00:00:00",
           end_time = "2023-01-18 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2023-01-15 00:00:00",
           end_time = "2023-01-18 00:00:00",
           Varibles = c("RDOsat_percent_5", "RDOsat_percent_9", "EXODOsat_percent_1"))

Pictures from the Camera

Could be ice near the far shore

Don’t see any ice in this picture and getting warm

Raining and no ice

Let’s check out Janurary 26th- 29th

Check out a few pictures from the Catwalk

Don’t see any ice in this picture and ducks swimming

Ducks in the foreground and no ice but cold

Hard to tell if there is ice but there is something strange in the middle of the picture

Raining and don’t see any ice

There appears to be a cold spell in the beginning of February

profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2023-02-04 00:00:00",
           end_time = "2023-02-07 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=FCR_Catwalk_EDI_2018_2023,
           start_time = "2023-02-04 00:00:00",
           end_time = "2023-02-07 00:00:00",
           Varibles = c("RDOsat_percent_5", "RDOsat_percent_9", "EXODOsat_percent_1"))

# Shortwave Down
weather<-FCR_met%>%
  filter(DateTime>ymd_hms("2023-02-04 00:00:00") & DateTime<ymd_hms("2023-02-07 00:00:00"))%>%
  ggplot(., aes(DateTime, ShortwaveRadiationDown_Average_W_m2))+
  geom_line()+
  scale_x_datetime(date_breaks = "2 day", date_minor_breaks = "1 day")+
  theme_bw()

weather

# Albedo
weather2<-FCR_met%>%
  filter(DateTime>ymd_hms("2023-02-04 00:00:00") & DateTime<ymd_hms("2023-02-07 00:00:00"))%>%
  ggplot(., aes(DateTime, Albedo_Average_W_m2))+
  geom_line()+
  scale_x_datetime(date_breaks = "2 day", date_minor_breaks = "1 day")+
  theme_bw()

weather2

Let’s see what the pictures from the Catwalk look like

Can’t tell if there is ice and the camera angle is different

Ducks on the water and can’t see any ice

Beaverdam

Checking the difference between the top and the bottom

BVR_platform_data_2020_2023%>%
  filter(DateTime>ymd_hms("2022-12-20 00:00:00") & DateTime<ymd_hms("2023-02-10 00:00:00"))%>%
  mutate(inverse=ThermistorTemp_C_5-ThermistorTemp_C_13)%>%
  mutate(inverse2=ThermistorTemp_C_6-ThermistorTemp_C_13)%>%
  select(DateTime, inverse, inverse2)%>%
  pivot_longer(!DateTime, names_to = "name", values_to = "obs")%>%
  ggplot(., aes(DateTime, obs, col=name))+
  geom_line()+
  geom_hline(yintercept=-0.1, linetype="dashed", color = "red")+
  scale_x_datetime(date_breaks = "5 day", date_minor_breaks = "1 day")+
  theme_bw()

Checking the Winter timeseries for when the difference between the top and the bottom is greater than -0.1. The red line “inverse” is the thermistor closest to the surface minus the bottom thermistor while “inverse 2” is the second highest thermistor minus the bottom one. The red dotted line is at -0.1 because the accuracy of the thermistors is 0.075.

After looking at the the timeseries let’s break it down for each period and look more closely at the temperature profiles, disolved oxygen profiles, and images from the camera at the catwalk.

Ice Period from December 20th-22nd

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2022-12-20 00:00:00",
           end_time = "2022-12-23 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2022-12-20 00:00:00",
           end_time = "2022-12-23 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from December 25th- January 3rd

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2022-12-25 00:00:00",
           end_time = "2023-01-04 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2022-12-25 00:00:00",
           end_time = "2023-01-04 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from January 10th-12th

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-10 00:00:00",
           end_time = "2023-01-13 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-10 00:00:00",
           end_time = "2023-01-13 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from January 16th-17th

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-16 00:00:00",
           end_time = "2023-01-18 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-16 00:00:00",
           end_time = "2023-01-18 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from January 21st-23rd and then Jaunary 24th-26th

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-21 00:00:00",
           end_time = "2023-01-27 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-21 00:00:00",
           end_time = "2023-01-27 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from January 28th-30th

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-28 00:00:00",
           end_time = "2023-01-30 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-01-28 00:00:00",
           end_time = "2023-01-30 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))

Ice Period from February 4th-6th

profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-02-4 00:00:00",
           end_time = "2023-02-07 00:00:00",
           Varibles = starts_with("Thermis"))

# DO
profile_plot(DATA=BVR_platform_data_2020_2023,
           start_time = "2023-02-04 00:00:00",
           end_time = "2023-02-07 00:00:00",
           Varibles = c("RDOsat_percent_6", "RDOsat_percent_13", "EXODOsat_percent_1.5"))